Question

How can I explain multivariate regression?

Answer 1

Multivariate Regression is a strategy used to quantify the degree at which more than one free factor (indicators) and more than one ward variable (reactions), are directly related. The technique is extensively used to anticipate the conduct of the reaction factors related to changes in the indicator factors, when an ideal level of connection has been set up. The Multivariate Regression model, relates more than one indicator and more than one reaction.   

Multivariate Regression is one of the most straightforward Machine Learning Algorithm. It goes under the class of Supervised Learning Algorithms i.e, when we are furnished with preparing dataset. A portion of the issues that can be unraveled utilizing this model are:

A scientist has gathered information on three mental factors, four scholastic factors (government sanctioned grades), and the sort of instructive program the understudy is in for 600 secondary school understudies. She is keen on how the arrangement of mental factors is identified with the scholastic factors and the sort of program the understudy is in.

A specialist has gathered information on cholesterol, pulse, and weight. She likewise gathered information on the dietary patterns of the subjects (e.g., what number of ounces of red meat, fish, dairy items, and chocolate expended every week). She needs to examine the connection between the three proportions of wellbeing and dietary patterns.

A property seller needs to set lodging costs which are based different components like Size of house, No of rooms, Age of house, and so forth .